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52 results for “information content”
Information content estimation output for specific humidity profiles
<p>Output of information content estimation based on optimal estimation theory <strong>[1]</strong>. Detailed descriptions of the information content estimation performed here can be found in Section 3.3 of <strong>[2]</strong>. The files have been created with the codes published on Github/Zenodo <strong>[3]</strong>.</p> <p>The cryptic file name suffixes _472, _481, _482, _483 and _484 represent different settings of the Neural Network retrieval to estimate the information content for different inputs:</p> <ul> <li>_472: TBs at all frequencies of the microwave radiometers HATPRO and MiRAC-P (instruments are described in <strong>[2]</strong>,<strong>[4]</strong>)</li> <li>_481: TBs only at K-band frequencies (22.24-31.4 GHz)</li> <li>_482: TBs at K- and V-band frequencies (22.24 - 58 GHz)</li> <li>_483: TBs at K- and G-band frequencies (22.24-31.4 GHz, 175.81-190.81 GHz)</li> <li>_484: TBs at K-, G-band and higher frequencies (22.24-31.4 GHz, 175.81-190.81 GHz, 243 GHz, 340 GHz)</li> </ul> <p>Detailed Neural Network settings can also be found in <strong>[2]</strong> and test_purpose.yaml in <strong>[3]</strong>.</p> <p>The file eval_info_content_idx.nc contains indices to consider a subset of the years 2001, 2006, 2011, 2015 of <strong>[5]</strong>, used as evaluation data in <strong>[2]</strong>, for the information content estimation. We did not use the full ERA5 evaluation data set because of computation time.</p> <p><strong>[1]:</strong> Rodgers, C. D.: Inverse methods for atmospheric sounding: theory and practice, no. 2 in Series on atmospheric, oceanic and planetary physics, World Scientific, Singapore, repr edn., ISBN 978-981-02-2740-1, 2008.</p> <p><strong>[2]:</strong> Walbröl, A., Griesche, H. J., Mech, M., Crewell, S., and Ebell, K.: Combining low- and high-frequency microwave radiometer measurements from the MOSAiC expedition for enhanced water vapour products, Atmospheric Measurement Techniques, 17, 6223-6245, https://doi.org/10.5194/amt-17-6223-2024, 2024.</p> <p><strong>[3]: </strong>Walbröl, A.: Codes for: Combining low and high frequency microwave radiometer measurements from the MOSAiC expedition for enhanced water vapour products (1.0.1). Zenodo. <a href="https://doi.org/10.5281/zenodo.11123136" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.11123136</a>, 2024.</p> <p><strong>[4]:</strong> Walbröl, A., Crewell, S., Engelmann, R., Orlandi, E., Griesche, H., Radenz, M., Hofer, J., Althausen, D., Maturilli, M., and Ebell, K.: Atmospheric temperature, water vapour and liquid water path from two microwave radiometers during MOSAiC, Scientific Data, 9, 534, https://doi.org/10.1038/s41597-022-01504-1, 2022.</p> <p><strong>[5]:</strong> Walbröl, A., and Mech, M.: ERA5 based training, validation and evaluation data for retrievals combining 22-58 GHz with 175-340 GHz microwave radiometer measurements during MOSAiC (1.0.0). Zenodo. https://doi.org/10.5281/zenodo.10997365, 2024.</p>
All-sky information content analysis for novel passive microwave instruments - data
<p>This dataset is the underlying data for the article:</p> <p>Grützun, V., S. A. Buehler, L. Kluft, M. Brath, J. Mendrok, and P. Eriksson (in press, 2018), All-sky Information Content Analysis for Novel Passive Microwave Instruments in the Range from 23.8 GHz up to 874.4 GHz, Atmos. Meas. Tech., doi:10.5194/amt-2017-377. </p> <p>Please refer to that article for a description of the scientific background of the data and to the attached README file for a technical documentation. </p> <p>Contact: Verena Grützun, verena.gruetzun@uni-hamburg.de<br> </p>
Gridded spatial information on soil organic carbon content, density and stock in Hungary for 1992 and 2000
<p>Predictive soil organic carbon (SOC) content, density, and stock maps, along with the associated prediction uncertainty, are provided for the years 1992 and 2000, for the entire territory of Hungary. The maps refer to the topsoils (0–30 cm) with a spatial resolution of 100⨯100 m. The uncertainty associated with the SOC property maps is expressed by the lower and upper limits of the 90% prediction interval (PI), the range of values within which the true value is expected to occur 9 times out of 10. This means that there are two maps to each SOC property map, quantifying its prediction uncertainty. It should be added that all maps have been masked with open water bodies, as these areas are not relevant for soils.</p> <p><strong>For more details / to cite this dataset please use:</strong></p> <p><a href="https://doi.org/10.1038/s41597-024-04158-3">Szatmári, G., Laborczi, A., Mészáros, J., Takács, K., Benő, A., Koós, S., Bakacsi, Z., & Pásztor, L. (2024). Gridded, temporally referenced spatial information on soil organic carbon for Hungary. Scientific Data 11, 1312.</a></p> <p><strong>Custom code used for digital soil mapping and validation is available on GitHub:</strong></p> <p><a href="https://github.com/GaborSzatmari/HU-SOC-mapping" target="_blank" rel="noopener">https://github.com/GaborSzatmari/HU-SOC-mapping</a></p> <p><strong>Description of the files:</strong></p> <p>The resulting maps are shared as GeoTIFF files. The coordinate reference system is the Hungarian Unified National Projection System (HD72/EOV; EPSG: 23700) (<a href="https://epsg.io/23700" target="_blank" rel="noopener">https://epsg.io/23700</a>). The table below provides further information on the published maps. Note that the first file (00_Overview.jpg) gives an overview of the SOC property maps.</p> <table> <tbody> <tr> <td> <p><strong>SOC property maps</strong></p> </td> <td> <p><strong>Unit</strong></p> </td> <td> <p><strong>Year</strong></p> </td> <td> <p><strong>Filename</strong></p> </td> </tr> <tr> <td> <p>SOC content map</p> </td> <td> <p>[g ∙ kg<sup>-1</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCc_0_30cm_1992_pred.tif</p> </td> </tr> <tr> <td> <p>SOC content, lower limit of the 90% PI</p> </td> <td> <p>[g ∙ kg<sup>-1</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCc_0_30cm_1992_q05.tif</p> </td> </tr> <tr> <td> <p>SOC content, upper limit of the 90% PI</p> </td> <td> <p>[g ∙ kg<sup>-1</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCc_0_30cm_1992_q95.tif</p> </td> </tr> <tr> <td> <p>SOC density map</p> </td> <td> <p>[kg ∙ m<sup>-3</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCd_0_30cm_1992_pred.tif</p> </td> </tr> <tr> <td> <p>SOC density, lower limit of the 90% PI</p> </td> <td> <p>[kg ∙ m<sup>-3</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCd_0_30cm_1992_q05.tif</p> </td> </tr> <tr> <td> <p>SOC density, upper limit of the 90% PI</p> </td> <td> <p>[kg ∙ m<sup>-3</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCd_0_30cm_1992_q95.tif</p> </td> </tr> <tr> <td> <p>SOC stock map</p> </td> <td> <p>[tons ∙ ha<sup>-1</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCs_0_30cm_1992_pred.tif</p> </td> </tr> <tr> <td> <p>SOC stock, lower limit of the 90% PI</p> </td> <td> <p>[tons ∙ ha<sup>-1</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCs_0_30cm_1992_q05.tif</p> </td> </tr> <tr> <td> <p>SOC stock, upper limit of the 90% PI</p> </td> <td> <p>[tons ∙ ha<sup>-1</sup>]</p> </td> <td> <p>1992</p> </td> <td> <p>SOCs_0_30cm_1992_q95.tif</p> </td> </tr> <tr> <td> <p>SOC content map</p> </td> <td> <p>[g ∙ kg<sup>-1</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCc_0_30cm_2000_pred.tif</p> </td> </tr> <tr> <td> <p>SOC content, lower limit of the 90% PI</p> </td> <td> <p>[g ∙ kg<sup>-1</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCc_0_30cm_2000_q05.tif</p> </td> </tr> <tr> <td> <p>SOC content, upper limit of the 90% PI</p> </td> <td> <p>[g ∙ kg<sup>-1</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCc_0_30cm_2000_q95.tif</p> </td> </tr> <tr> <td> <p>SOC density map</p> </td> <td> <p>[kg ∙ m<sup>-3</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCd_0_30cm_2000_pred.tif</p> </td> </tr> <tr> <td> <p>SOC density, lower limit of the 90% PI</p> </td> <td> <p>[kg ∙ m<sup>-3</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCd_0_30cm_2000_q05.tif</p> </td> </tr> <tr> <td> <p>SOC density, upper limit of the 90% PI</p> </td> <td> <p>[kg ∙ m<sup>-3</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCd_0_30cm_2000_q95.tif</p> </td> </tr> <tr> <td> <p>SOC stock map</p> </td> <td> <p>[tons ∙ ha<sup>-1</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCs_0_30cm_2000_pred.tif</p> </td> </tr> <tr> <td> <p>SOC stock, lower limit of the 90% PI</p> </td> <td> <p>[tons ∙ ha<sup>-1</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCs_0_30cm_2000_q05.tif</p> </td> </tr> <tr> <td> <p>SOC stock, upper limit of the 90% PI</p> </td> <td> <p>[tons ∙ ha<sup>-1</sup>]</p> </td> <td> <p>2000</p> </td> <td> <p>SOCs_0_30cm_2000_q95.tif</p> </td> </tr> </tbody> </table> <p> </p>
Dataset: Information content of ultraviolet-reflecting color patches and visual perception of body coloration in the Tyrrhenian wall lizard Podarcis tiliguerta
<p>These are the data sets and R script corresponding to the scientific publication with the same title and authors.</p> <p>Description of these files is available in the file Note.pdf</p>
EduQuick: A Dataset for Assessing Summarization of Informal Educational Content for Social Media
<p>The presented dataset is a curated collection of model-generated text for educational TikTok content, abbreviated as EduQuick. This dataset is the result of evaluating and selecting high-quality content generated by the GPT-4 model following an empirical study. It aims to provide engaging and informative summaries suitable for TikTok's educational audience.</p>
Data archive for the peer-reviewed journal article "Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data"
<p>Data archive accompanying the peer-reviewed journal article "Information content and aerosol property retrieval potential for different types of in situ polar nephelometer data". This article was accepted for publication in the journal <em>Atmospheric Measurement Techniques</em> in 2022. The original contributions presented in the study are included in the article and its supplementary information. The GRASP-OPEN model was used to perform forward calculations: this model is publicly available on the official GRASP website (https://www.grasp-open.com/; last access: 14 September, 2022). The specific GRASP-OPEN model outputs that were used for the study are contained in this data archive. </p>
Processed data from "Chromatin information content landscapes inform transcription factor and DNA interactions"
<p><strong>Chromatin information content landscapes inform transcription factor and DNA interactions</strong></p> <p>Authors: Ricardo D’Oliveira Albanus, Yasuhiro Kyono, John Hensley, Arushi Varshney, Peter Orchard, Jacob O. Kitzman, Stephen C. J. Parker</p> <p><a href="https://doi.org/10.1101/777532">https://doi.org/10.1101/777532</a></p> <p> </p> <p>This record contains the processed data used in our manuscript. For instructions on how to use or regenerate this data, please refer to <a href="https://github.com/ParkerLab/chromatin_information">https://github.com/ParkerLab/chromatin_information</a>.</p>
Analyzing variational quantum landscapes with information content
<p>This repository contains the code, data and notebooks to reproduce the figures of "Analyzing variational quantum landscapes with information content".</p>
Experimental materials for "The Effect of Information Content and Length on Name Recollection"
<p>Experimental materials for the paper "The Effect of Information Content and Length on Name Recollection" published in the 30th IEEE/ACM International Conference on Program Comprehension (ICPC), 16-17 May 2022.</p> <p>Includes the experimental materials, responses of participants in the experiments, and analysis scripts and results for the two experiments described in the paper.</p>
Data from: Assessing bayesian phylogenetic information content of morphological data using knowledge from anatomy ontologies
<p>Morphology remains a primary source of phylogenetic information for many groups of organisms, and the only one for most fossil taxa. Organismal anatomy is not a collection of randomly assembled and independent 'parts', but instead a set of dependent and hierarchically nested entities resulting from ontogeny and phylogeny. How do we make sense of these dependent and at times redundant characters? One promising approach is using ontologies—structured controlled vocabularies that summarize knowledge about different properties of anatomical entities, including developmental and structural dependencies. Here we assess whether the proximity of ontology-annotated characters within an ontology predicts evolutionary patterns. To do so, we measure phylogenetic information across characters and evaluate if it is hierarchically structured by ontological knowledge—in much the same way as phylogeny structures across-species diversity. We implement an approach to evaluate the Bayesian phylogenetic information (BPI) content and phylogenetic dissonance among ontology-annotated anatomical data subsets. We applied this to datasets representing two disparate animal groups: bees (Hexapoda: Hymenoptera: Apoidea, 209 chars) and characiform fishes (Actinopterygii: Ostariophysi: Characiformes, 463 chars). For bees, we find that BPI is not substantially structured by anatomy since dissonance is often high among morphologically related anatomical entities. For fishes, we find substantial information for two clusters of anatomical entities instantiating concepts from the jaws and branchial arch bones, but among-subset information decreases and dissonance increases substantially moving to higher level subsets in the ontology. We further applied our approach to address particular evolutionary hypotheses with an example of morphological evolution in miniature fishes. While we show that ontology does indeed structure phylogenetic information, additional relationships and processes, such as convergence, likely play a substantial role in explaining BPI and dissonance, and merit future investigation. Our work demonstrates how complex morphological datasets can be interrogated with ontologies by allowing one to access how information is spread hierarchically across anatomical concepts, how congruent this information is, and what sorts of processes may structure it: phylogeny, development, or convergence.</p>
Supplementary Online Content to "Alterity marking and enhancing accessibility in lexical borrowing: Meta-information techniques in the use of incipient anglicisms in French and Italian"
<ul> <li>Overview of newspaper articles analysed in Sections 4 and 5</li> <li>Sources of the newspaper articles</li> <li>Sample analyses of the use of meta-information techniques in F2 and I3</li> </ul>
Data for: Increasing information content and diagnosability in family-level classifications
<p>Higher-level classifications often must account for monotypic taxa representing depauperate evolutionary lineages and lacking synapomorphies of their better-known, well-defined sister clades. In a ranked (Linnean) or unranked (phylogenetic) classification system, discovering such a depauperate taxon does not necessarily invalidate the rank classification of sister clades. Named higher taxa must be monophyletic to be phylogenetically valid. Ranked taxa above the species level should also maximize information content, diagnosability, and utility (e.g., in biodiversity conservation). In spider classification, families are the highest rank that is systematically catalogued, and <em>incertae</em> <em>sedis</em> is not allowed. Consequently, it is important that family-level taxa be well-defined and informative. We revisit the classification problem of Orbipurae, an unranked suprafamilial clade containing the spider families Nephilidae, Phonognathidae, and Araneidae <em>sensu</em> <em>stricto</em>. We argue that, to maximize diagnosability, information content, conservation utility, and practical taxonomic considerations, this "splitting" scheme is superior to its recently proposed alternative, which lumps these families together as Araneidae <em>sensu</em> <em>lato</em>. We propose to redefine Araneidae and recognize a monogeneric spider family, Paraplectanoididae fam. nov. to accommodate the depauperate lineage <em>Paraplectanoides</em>. We present new subgenomic data to stabilize Orbipurae topology which also supports our proposed family-level classification. Our example from spiders demonstrates why classifications must be able to accommodate depauperate evolutionary lineages, e.g., <em>Paraplectanoides</em>. Finally, although clade age should not be a criterion to determine rank, other things being equal, comparable ages of similarly ranked taxa do benefit comparative biology.</p>
Data for: Increasing information content and diagnosability in family-level classifications
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Data from: The influence of locus number and information content on species delimitation: an empirical test case in an endangered Mexican salamander
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Data from: Assessing bayesian phylogenetic information content of morphological data using knowledge from anatomy ontologies
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Experts views on information evaluation and verification: source reliability, content credibility and audiovisual material checking
<p>Experts can be asked about nformation evaluation and verification: source reliability, content credibility and audiovisual material checking.</p> <p>OER available at: <a href="https://multimedia.ciberimaginario.es/genially/2020/CRESCEnt/4.2.1/">https://multimedia.ciberimaginario.es/genially/2020/CRESCEnt/4.2.1/</a> </p>
Data from: SNPs selected by information content outperform randomly selected microsatellite loci for delineating genetic identification and introgression in the endangered dark European honeybee (Apis mellifera mellifera)
The honeybee (Apis mellifera) has been threatened by multiple factors, including pests and pathogens, pesticides, and loss of locally adapted gene complexes due to replacement and introgression. In western Europe, the genetic integrity of the native A.m. mellifera (M-lineage) is endangered due to trading and intensive queen breeding with commercial subspecies of eastern European ancestry (C-lineage). Effective conservation actions require reliable molecular tools to identify purebred A.m. mellifera colonies. Microsatellites have been preferred for identification of A.m. mellifera stocks across conservation centers. However, owing to high-throughput, easy transferability between laboratories and low genotyping error, SNPs promise to become popular. Here, we compared the resolving power of a widely utilized microsatellite dataset to detect structure and introgression with that of different datasets that combine a variable number of SNPs selected for their information content and genomic proximity to the microsatellites. Contrary to every SNP dataset, microsatellites were unable to clearly separate the two European lineages in the PCA space. Mean introgression proportions were identical across the two marker types, although at the individual level microsatellites' performance was relatively poor at the upper range of introgression, a result reflected by their lower precision. Although mean accuracy was relatively high across datasets (>91%), microsatellites were the least accurate and the top-ranked informative 144 SNPs were the most accurate. Comparisons amongst the SNP datasets showed that those combining SNPs flanking microsatellites performed worst. Our results suggest that SNPs are more powerful for identification of A.m. mellifera colonies, especially when they are selected by information content.
Data of Paper "Turning a Multilingual Historical Archive into an Information System through Post-OCR Correction and Content-Based Indexation"
<p>We evaluated our approach on a collection of 946 historical documents belonging to the Biblioteca Nacional de Catalunya (BNC), spanning from 1914 to 1951. Each document is the issue of a magazine, comprising different articles by different authors. This implies that, despite the thematic nature of magazines and specific issues, there is a certain degree of heterogeneity in each document. Magazines were selected based on their relevance w.r.t. art in general and, more specifically, early 20th century avant-garde movements (e.g., Dadaism, Cubism, etc.). For each document, we have the scanning of the original artifact and the plain raw text extracted through ABBYY FineReader OCR tool. To the best of our knowledge, this is the first Catalan-dominated OCR corpus ever released. </p>
The first comprehensive revision of all the species attributed to Melomys led J. I. Menzies in 1996 to resurrect the genus Paramelomys and to redefine its morphologicallimits and species content. Menzies created P. gressitti as a new species belonging to a group displaying morphological similarities and including also P. lorentzii and P. moncktoni. Monotypic Distribution. E New Guinea. Descriptive notes. Head-body 135-162 mm, hindfoot 30-34 mm; no specific data are available for body weight. Gressitt's Mosaic-tailed Rat is a medium-sized Paramelomys with a soft, thick and woolly pelage, a long narrow foot, and a tail with three hairs per scale. It exhibits a medium-sepia dorsal pelage and a gray-buff ventral one. Tail is slightly shorter (99%) than head-body length. The skull has a narrow zygomatic plate. Habitat. Moist tropical mountain forest between 2300 m and 2400 m. Food and Feeding. No information. Breeding. No information. Activity patterns. Gressitt's Mosaic-tailed Rat is terrestrial. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Endangered on The IUCN Red List owing to its small geographic range (less than 3500 km?*) and the destruction ofits habitat by mining and logging activities. The major threat to Gressitt's Mosaic-tailed Rat is ongoing habitat degradation caused by nearby human populations; habitat on Mount Kandy has been destroyed by gold-miners and wood-cutters. Bibliography. Menzies (1996). in Muridae
The first comprehensive revision of all the species attributed to Melomys led J. I. Menzies in 1996 to resurrect the genus Paramelomys and to redefine its morphologicallimits and species content. Menzies created P. gressitti as a new species belonging to a group displaying morphological similarities and including also P. lorentzii and P. moncktoni. Monotypic Distribution. E New Guinea. Descriptive notes. Head-body 135-162 mm, hindfoot 30-34 mm; no specific data are available for body weight. Gressitt's Mosaic-tailed Rat is a medium-sized Paramelomys with a soft, thick and woolly pelage, a long narrow foot, and a tail with three hairs per scale. It exhibits a medium-sepia dorsal pelage and a gray-buff ventral one. Tail is slightly shorter (99%) than head-body length. The skull has a narrow zygomatic plate. Habitat. Moist tropical mountain forest between 2300 m and 2400 m. Food and Feeding. No information. Breeding. No information. Activity patterns. Gressitt's Mosaic-tailed Rat is terrestrial. Movements, Home range and Social organization. No information. Status and Conservation. Classified as Endangered on The IUCN Red List owing to its small geographic range (less than 3500 km?*) and the destruction ofits habitat by mining and logging activities. The major threat to Gressitt's Mosaic-tailed Rat is ongoing habitat degradation caused by nearby human populations; habitat on Mount Kandy has been destroyed by gold-miners and wood-cutters. Bibliography. Menzies (1996).
Supplementary Material for "Phylogeny Inference Under Time-Decaying Migration and Varying Information Content"
<p>This upload compirises XML files containing sequence information for the Anopheles gambiae group of African mosquitoes. The data were originally published in Fontaine et al. (2015), and were subsequently curated and modified by Thawornwattana et al. (2018), a subset of which we used in our upcoming work.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.